Restoranlardaki Hizmet Robotları: TCCM Çerçevesinin Kullanıldığı Sistematik Bir Literatür İncelemesi

Year 2025, Volume: 28 Issue: 2, 498 - 516, 30.11.2025

Kadir Özdemir , Çağatan Taşkın

Abstract

Bu çalışma, SPAR-4-SLR protokolüne dayalı TCCM (Teoriler-Bağlam-Karakteristikler-Metodoloji) çerçevesini ve bibliyometrik analiz yöntemini kullanarak restoranlardaki hizmet robotları hakkındaki akademik literatürü analiz etmeyi amaçlamaktadır. Sistematik literatür incelemesi için WOS ve SCOPUS veri tabanlarından yararlanılmıştır. Hariç tutma ve dahil etme kriterleri uygulandıktan sonra elde edilen makalelerin performans analizi Bibliometrix R uygulması kullanılarak gerçekleştirilmiştir. Sonuçlara göre, antropomorfizm teorisi, tekinsiz vadi teorisi, TAM, rol uyumu teorisi ve UTAUT incelenen çalışmalarda en sık kullanılan teorilerdir. Çin, ABD ve Kore en fazla makaleye sahip ülkelerdir. Ancak, yazarlar çoğunlukla tek bir ülkedendir. İnceleme sonucu oluşturulan kavramsal çerçeveye göre, sıklıkla kullanılan değişkenler tüketici karakteristiği, robotla ilgili ve tüketici algısıyla ilgili değişkenler olarak sınıflandırılmıştır. PROCESS Macro, Yapısal Eşitlik Modellemesi, PLS/SEM, ANOVA ve ANCOVA en yaygın kullanılan analiz yöntemleridir. İncelenen çalışmalardaki veriler ağırlıklı olarak senaryo analizli bir anket aracılığıyla toplanmıştır. Bu çalışma, gelecekteki araştırmalara rehberlik etmek, yapılacak çalışmalar için alanlar belirlemek ve gelişmekte olan araştırma alanını ilerletmek için içgörüler sunmaktadır. Son olarak, bu çalışma akademisyenlere, hizmet sağlayıcılara, yöneticilere ve girişimcilere değerli teorik ve pratik bilgiler sağlamakta ve kılavuzluk etmektedir.

Keywords

Hizmet Robotları , Restoranlar , TCCM Çerçevesi , Sistematik Literatür İncelemesi , Bibliyometrik Analiz

Service Robots in the Restaurants: A Systematic Literature Review Using TCCM Framework

Abstract

This study aims to analyze academic literature on service robots in restaurants using the TCCM framework and bibliometric analysis based on the SPAR-4-SLR protocol. A systematic literature review utilized the WOS and SCOPUS databases. The performance analysis of the articles obtained after applying the exclusion and inclusion criteria was carried out using Bibliometrix R studio. According to the results, anthropomorphism theory, uncanny valley theory, TAM, role congruence theory, and UTAUT are the most frequently used theories in the reviewed studies. China, the USA, and Korea have the highest number of articles. However, the authors are primarily from a single country. According to the conceptual framework, the frequently used variables are classified as consumer characteristics, robot-related, and consumer perception-related. PROCESS Macro, Structural Equation Modeling, PLS/SEM, ANOVA, and ANCOVA are the most widely used analysis methods. The data in the reviewed studies were predominantly collected via a questionnaire with scenario analysis. This study offers insights to guide future research, identify promising areas for further investigation, and advance the emerging research field. Finally, this study will provide scholars, service providers, managers, and entrepreneurs with valuable theoretical and practical insights and guidelines.

Keywords

Service Robots , Restaurants , TCCM Framework , Systematic Literature Review , Bibliometric Analysis

References

• Ahiadu, A. A., & Abidoye, R. B. (2024). Economic uncertainty and direct property performance: a systematic review using the SPAR-4-SLR protocol. Journal of Property Investment & Finance, 42(1), 89-111.
• Akdim, K., Belanche, D., & Flavián, M. (2023). Attitudes toward service robots: analyses of explicit and implicit attitudes based on anthropomorphism and construal level theory. International Journal of Contemporary Hospitality Management, 35(8), 2816-2837.
• Australian Strategic Policy Institute (ASPI), (2023). "ASPI's Critical Technology Tracker - The global race for future power", available at: https://www.aspi.org.au/report/critical-technology-tracker. (Accessed 05 November 2024).
• Becker, M., Mahr, D., & Odekerken-Schröder, G. (2023). Customer comfort during service robot interactions. Service Business, 17(1), 137-165.
• Belanche, D., Casaló, L. V., Flavián, C., & Schepers, J. (2020). Robots or frontline employees? Exploring customers' attributions of responsibility and stability after service failure or success. Journal of Service Management, 31(2), 267-289.
• Belanche, D., Casaló, L. V., Schepers, J., & Flavián, C. (2021). Examining the effects of robots' physical appearance, warmth, and competence in frontline services: The Humanness‐Value‐Loyalty model. Psychology & Marketing, 38(12), 2357-2376.
• Bhaiswar, R., Chawla, D., & Meenakshi, N. (2022). The influence of eWOM communications on intended online purchases: a literature review using TCCM framework and future research agenda. International Journal of Indian Culture and Business Management, 26(3), 328-361.
• Brunner, C. B., Ullrich, S., & De Oliveira, M. J. (2019). The most optimal way to deal with negative consumer review: can positive brand and customer responses rebuild product purchase intentions?. Internet Research, 29(1), 104-122.
• Cain, L. N., Thomas, J. H., & Alonso Jr, M. (2019). From sci-fi to sci-fact: the state of robotics and AI in the hospitality industry. Journal of Hospitality and Tourism Technology, 10(4), 624-650.
• Cha, S. S. (2020). Customers' intention to use robot-serviced restaurants in Korea: relationship of coolness and MCI factors. International Journal of Contemporary Hospitality Management, 32(9), 2947-2968.
• Chang, W., & Kim, K. K. (2022). Appropriate service robots in exchange and communal relationships. Journal of Business Research, 141, 462-474.
• Chen, C. F., & VG, G. (2023). Antecedents and outcomes of use experience of airport service robot: The stimulus-organism-response (SOR) framework. Journal of Vacation Marketing, 29(4), 570-583.
• Cheong, F., Huang, Q., Ye, H., & Law, R. (2023). Application and Consequences of Service Robots in Tourism and Hospitality Scenarios: A Systematic Literature Review. Journal of Quality Assurance in Hospitality & Tourism, 1-23.
• Choi, S., Liu, S. Q., & Mattila, A. S. (2019). "How may I help you?" Says a robot: examining language styles in the service encounter. International Journal of Hospitality Management, 82, 32-38.
• Choi, S., Mattila, A. S., & Bolton, L. E. (2021). To err is human (-oid): how do consumers react to robot service failure and recovery?. Journal of Service Research, 24(3), 354-371.
• Choi, M., Choi, Y., Kim, S., & Badu-Baiden, F. (2023). Human vs robot baristas during the COVID-19 pandemic: effects of masks and vaccines on perceived safety and visit intention. International Journal of Contemporary Hospitality Management, 35(2), 469-491.
• Chuah, S. H. W., Jitanugoon, S., Puntha, P., & Aw, E. C. X. (2022). You don't have to tip the human waiters anymore, but… Unveiling factors that influence consumers' willingness to pay a price premium for robotic restaurants. International Journal of Contemporary Hospitality Management, 34(10), 3553-3587.
• Cobelli, N., & Blasioli, E. (2023). To be or not to be digital? A bibliometric analysis of adoption of Health services. The TQM Journal, 35 (9), 299-331.
• Coelho, E. C. D. S., & Farias, J. S. (2024). Value cocreation and codestruction in artificial intelligence-enabled service interactions: literature review and research agenda. Spanish Journal of Marketing-ESIC.
• Das, M., Roy, A., Paul, J., & Saha, V. (2022). High and low impulsive buying in social commerce: A SPAR-4-SLR and fsQCA approach. IEEE Transactions on Engineering Management. 1-15.
• Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 318– 339
• De Kervenoael, R., Hasan, R., Schwob, A., & Goh, E. (2020). Leveraging human-robot interaction in hospitality services: Incorporating the role of perceived value, empathy, and information sharing into visitors' intentions to use social robots. Tourism Management, 78, 104042.
• Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285-296.
• Epley, N., Waytz, A. & Cacioppo, J.T. (2007). On seeing human: a three-factor theory of anthropomorphism, Psychological Review, Vol. 114 No. 4, 864-886.
• Fusté-Forné, F. (2021). Robot chefs in gastronomy tourism: what's on the menu?. Tourism Management Perspectives, 37, 100774.
• Fusté-Forné, F., & Ivanov, S. (2021). Robots in service experiences: Negotiating food tourism in pandemic futures. Journal of Tourism Futures, 7(3), 303-310.
• Gonzalez, R., Gasco, J., & Llopis, J. (2022). Information and communication technologies in food services and restaurants: a systematic review. International Journal of Contemporary Hospitality Management, 34(4), 1423-1447.
• Hu, Y. (2021). An improvement or a gimmick? The importance of user perceived values, previous experience, and industry context in human–robot service interaction. Journal of Destination Marketing & Management, 21, 100645.
• Huang, M. H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155-172.
• Huang, H., & Liu, S. Q. (2022). Are consumers more attracted to restaurants featuring humanoid or non-humanoid service robots?. International Journal of Hospitality Management, 107, 103310.
• Hwang, J., Kim, H. M., & Kim, I. (2022). The antecedent and consequences of brand competence: Focusing on the moderating role of the type of server in the restaurant industry. Journal of Hospitality and Tourism Management, 50, 337-344.
• Ivanov, S., Gretzel, U., Berezina, K., Sigala, M., & Webster, C. (2019). Progress on robotics in hospitality and tourism: a review of the literature. Journal of Hospitality and Tourism Technology, 10(4), 489-521.
• Kao, W. K., & Huang, Y. S. S. (2023). Service robots in full-and limited-service restaurants: Extending technology acceptance model. Journal of Hospitality and Tourism Management, 54, 10-21.
• Khan, F. M., Anas, M., & Uddin, S. F. (2024). Anthropomorphism and consumer behavior: A SPAR‐4‐SLR protocol compliant hybrid review. International Journal of Consumer Studies, 48(1), e12985.
• Kim, T., Jo, H., Yhee, Y., & Koo, C. (2022). Robots, artificial intelligence, and service automation (RAISA) in hospitality: sentiment analysis of YouTube streaming data. Electronic Markets, 32(1), 259-275.
• Lee, I. (2021). Service robots: A Systematic Literature Review. Electronics, 10(21), 2658.
• Leung, R. (2019). Smart hospitality: Taiwan hotel stakeholder perspectives. Tourism Review, 74(1), 50-62.
• Li, Y., & Wang, C. (2022). Effect of customer's perception on service robot acceptance. International Journal of Consumer Studies, 46(4), 1241-1261.
• Lim, X. J., Chang, J. Y. S., Cheah, J. H., Lim, W. M., Kraus, S., & Dabić, M. (2024). Out of the way, human! Understanding post-adoption of last-mile delivery robots. Technological forecasting and social change, 201, 123242.
• Lin, Y. (2023). Consumer Responses to Service Robots-From Pre-Interaction to Post-Interaction.
• Liu, D., Li, C., Zhang, J., & Huang, W. (2023). Robot service failure and recovery: Literature review and future directions. International Journal of Advanced Robotic Systems, 20(4), 17298806231191606.
• Lu, L., Cai, R., & Gursoy, D. (2019). Developing and validating a service robot integration willingness scale. International Journal of Hospitality Management, 80, 36-51.
• Lu, V. N., Wirtz, J., Kunz, W. H., Paluch, S., Gruber, T., Martins, A., & Patterson, P. G. (2020). Service robots, customers and service employees: what can we learn from the academic literature and where are the gaps?. Journal of Service Theory and Practice, 30(3), 361-391.
• Lucas, E.R. (1988). On the mechanics of economic development. Journal of Monetary Economics, 22 (1), 3-42.
• Ma, E., Yang, H., Wang, Y. C., & Song, H. (2022). Building restaurant customers' technology readiness through robot-assisted experiences at multiple product levels. Tourism Management, 93, 104610.
• Mara, M., Appel, M., & Gnambs, T. (2022). Human-like robots and the uncanny valley. Zeitschrift für Psychologie. 230(1), 33-46.
• Markets & Markets (2024), "Service Robotics Industry worth $84.8 billion by 2028", available at: https://www.marketsandmarkets.com/PressReleases/service-robotics.asp. (Accessed 12 April 2024).
• McCartney, G., & McCartney, A. (2020). Rise of the machines: towards a conceptual service-robot research framework for the hospitality and tourism industry. International Journal of Contemporary Hospitality Management, 32(12), 3835-3851.
• McLeay, F., Osburg, V. S., Yoganathan, V., & Patterson, A. (2021). Replaced by a Robot: Service Implications in the Age of the Machine. Journal of Service Research, 24(1), 104-121.
• Mejia, C., Crandell, H. A., Broker, E., & Shoss, M. (2024). Working with service robots in the dining room: Employees' perspectives and realities. Journal of Hospitality and Tourism Technology.
• Mende, M., Scott, M. L., Van Doorn, J., Grewal, D., & Shanks, I. (2019). Service robots rising: How humanoid robots influence service experiences and elicit compensatory consumer responses. Journal of Marketing Research, 56(4), 535-556.
• Misselhorn, C. (2009). Empathy with inanimate objects and the uncanny valley. Minds and Machines, 19, 345-359.
• Moliner-Tena, M. A., Callarisa-Fiol, L. J., Sánchez-García, J., & Rodríguez-Artola, R. M. (2024). Co-creation 5.0: The frontline employee–robot team and firms' outcomes. The Tin Woodman paradox. Journal of Innovation & Knowledge, 9(3), 100534.
• Moral-Munoz, J. A. M., Viedma, E. H., Espejo, A. L. S., & Cobo, M. J. (2020). Software tools for conducting bibliometric analysis in science: An up-to-date review. El Profesional De La Informacion, 29 (1), 4.
• Mori, M. (1970). The uncanny valley, Energy, 7 (4), 33-35.
• Mukherjee, S., Baral, M. M., Nagariya, R., Venkataiah, C., Rao, U. A., & Rao, K. S. (2023). Systematic literature review and future research directions for service robots in hospitality and tourism industries. The Service Industries Journal, 43(15-16), 1083-1116.
• Odekerken-Schröder, G., Mennens, K., Steins, M., & Mahr, D. (2022). The service triad: an empirical study of service robots, customers and frontline employees. Journal of Service Management, 33(2), 246-292.
• Patwary, A. K., Hossain, M. S., Mistry, T. G., & Parvez, M. O. (2024). Enhancing service adaptability: a moderated mediation model of workplace ostracism, robot anthropomorphism, employees' readiness to change, and performance efficacy. Journal of Hospitality and Tourism Technology, (ahead-of-print).
• Paul, J., Lim, W. M., O'Cass, A., Hao, A. W., & Bresciani, S. (2021). Scientific procedures and rationales for systematic literature reviews (SPAR‐4‐SLR). International Journal of Consumer Studies, 45 (4), 1-16.
• Pransky, J. (1996), "Service robots–how we should define them?", Service Robot: An International Journal, 2(1), 4-5.
• Provenrobotics.ai. (2023). Seven examples of robot waiters in restaurants. https://provenrobotics.ai/robot-waiters-in-restaurants/, (Accessed 5 November 2024).
• Qiu, H., Li, M., Shu, B., & Bai, B. (2020). Enhancing hospitality experience with service robots: The mediating role of rapport building. Journal of Hospitality Marketing & Management, 29(3), 247-268.
• Rancati, G., & Maggioni, I. (2023). Neurophysiological responses to robot–human interactions in retail stores. Journal of Services Marketing, 37(3), 261-275.
• Rasheed, H. M. W., He, Y., Khizar, H. M. U., & Abbas, H. S. M. (2023). Exploring Consumer-Robot interaction in the hospitality sector: Unpacking the reasons for adoption (or resistance) to artificial intelligence. Technological Forecasting and Social Change, 192, 122555.
• Rosete, A., Soares, B., Salvadorinho, J., Reis, J., & Amorim, M. (2020). Service robots in the hospitality industry: An exploratory literature review. In Exploring Service Science: 10th International Conference, IESS 2020, Porto, Portugal, February 5–7, 2020, Proceedings 10 (pp. 174-186). Springer International Publishing.
• Roy Bhattacharjee, D., Pradhan, D., & Swani, K. (2022). Brand communities: A literature review and future research agendas using TCCM approach. International Journal of Consumer Studies, 46(1), 3-28.
• Saravanan, T. (2020). Evaluating the effectiveness of keyword, phrase, Boolean operator [AND] in bibliographic data access and retrieval for the subject chemistry. Library Philosophy and Practice, 1-18.
• Schraft, R.D. & Wanner, M.C. (1993). The aircraft cleaning robot 'SKYWASH'", Industrial Robot: An International Journal, 20 (6), 21-24.
• Seo, K. H., & Lee, J. H. (2021). The emergence of service robots at restaurants: Integrating trust, perceived risk, and satisfaction. Sustainability, 13(8), 4431.
• Shah, T. R., Kautish, P., & Mehmood, K. (2023). Influence of robots service quality on customers' acceptance in restaurants. Asia Pacific Journal of Marketing and Logistics, 35(12), 3117-3137.
• Shan, M., Zhu, Z., Chen, H., & Sun, S. (2024). Service robot's responses in service recovery and service evaluation: the moderating role of robots' social perception. Journal of Hospitality Marketing & Management, 33(2), 145-168.
• Shanks, I., Scott, M. L., Mende, M., van Doorn, J., & Grewal, D. (2024). Cobotic service teams and power dynamics: Understanding and mitigating unintended consequences of human-robot collaboration in healthcare services. Journal of the Academy of Marketing Science, 1-27.
• Sharma, N., Sharma, A., Dutta, N., & Priya, P. (2023). Showrooming: a retrospective and prospective review using the SPAR-4-SLR methodological framework. International Journal of Retail & Distribution Management.
• Shin, H. (2022). A critical review of robot research and future research opportunities: adopting a service ecosystem perspective. International Journal of Contemporary Hospitality Management, 34(6), 2337-2358.
• Singh, S., & Dhir, S. (2019). Structured review using TCCM and bibliometric analysis of international cause-related marketing, social marketing, and innovation of the firm. International Review on Public and Nonprofit Marketing, 16, 335-347.
• Söderlund, M. (2021). The robot-to-robot service encounter: an examination of the impact of inter-robot warmth. Journal of Services Marketing, 35(9), 15-27.
• Tuomi, A., Tussyadiah, I. P., & Hanna, P. (2021). Spicing up hospitality service encounters: the case of Pepper™. International Journal of Contemporary Hospitality Management, 33(11), 3906-3925.
• Van Pinxteren, M. M., Wetzels, R. W., Rüger, J., Pluymaekers, M., & Wetzels, M. (2019). Trust in humanoid robots: implications for services marketing. Journal of Services Marketing, 33(4), 507-518.
• Wang, Y. C., & Papastathopoulos, A. (2023). Cross-segment validation of customer support for AI-based service robots at luxury, fine-dining, casual, and quick-service restaurants. International Journal of Contemporary Hospitality Management.
• Wirtz, J., Patterson, P. G., Kunz, W. H., Gruber, T., Lu, V. N., Paluch, S., & Martins, A. (2018). Brave new world: service robots in the frontline. Journal of Service Management, 29(5), 907-931.
• Wirtz, J., Kunz, W., & Paluch, S. (2021). The service revolution, intelligent automation and service robots. European Business Review, 29(5), 909.
• Xie, L., & Lei, S. (2022). The nonlinear effect of service robot anthropomorphism on customers' usage intention: A privacy calculus perspective. International Journal of Hospitality Management, 107, 103312.
• Xu, J., Hsiao, A., Reid, S., & Ma, E. (2023). Working with service robots? A systematic literature review of hospitality employees' perspectives. International Journal of Hospitality Management, 113, 103523.
• Yörük, T., Akar, N., & Özmen, N. V. (2023). Research trends on guest experience with service robots in the hospitality industry: A bibliometric analysis. European Journal of Innovation Management.
• Zhang, X., Balaji, M. S., & Jiang, Y. (2022a). Robots at your service: value facilitation and value co-creation in restaurants. International Journal of Contemporary Hospitality Management, 34(5), 2004-2025.
• Zhang, W., Slade, E. L., & Pantano, E. (2024). Humanlike service robots: A systematic literature review and research agenda. Psychology & Marketing.
• Zhu, D. H., & Chang, Y. P. (2020). Robot with humanoid hands cooks food better? Effect of robotic chef anthropomorphism on food quality prediction. International Journal of Contemporary Hospitality Management, 32(3), 1367-1383.
• Zhu, D. H., & Zhang, W. Q. (2024). Do we have to know the hen that lays the eggs? How the disclosure timing of robot chef identity affects consumer perceived ethicality. Journal of Sustainable Tourism, 32(10), 2080-2097.